This article examines the current trend toward solving issues of procurement and processing of publicly disclosed pollution source data in China, where this data is characterized by heterogeneity and lack of standardization. Through ethnography and software analysis, the article examines the hidden labor entailed in automation using the case study of a Chinese e-NGO. We identify the bulk of this labor in “datascape navigation”, or the practices needed to locate, acquire and process the desired information within the infrastructure enabling the circulation of the data. The aspects of this labor are examined in relation to two data flows: enterprise environmental supervision records and information about real-time emissions. We identify several forms of unpredicted human and non-human labor entailed by both unsuccessful and successful automation attempts. We conclude that the labor involved by software automation of environmental data procurement and processing can critically impact environmental disclosure timing and quality.

Tarantino, M., Navigating a datascape: challenges in automating environmental data disclosure in China, <<JOURNAL OF ENVIRONMENTAL PLANNING AND MANAGEMENT>>, 2019; (N/A): 1-20. [doi:10.1080/09640568.2019.1659132] [http://hdl.handle.net/10807/142895]

Navigating a datascape: challenges in automating environmental data disclosure in China

MATTEO TARANTINO
2019

Abstract

This article examines the current trend toward solving issues of procurement and processing of publicly disclosed pollution source data in China, where this data is characterized by heterogeneity and lack of standardization. Through ethnography and software analysis, the article examines the hidden labor entailed in automation using the case study of a Chinese e-NGO. We identify the bulk of this labor in “datascape navigation”, or the practices needed to locate, acquire and process the desired information within the infrastructure enabling the circulation of the data. The aspects of this labor are examined in relation to two data flows: enterprise environmental supervision records and information about real-time emissions. We identify several forms of unpredicted human and non-human labor entailed by both unsuccessful and successful automation attempts. We conclude that the labor involved by software automation of environmental data procurement and processing can critically impact environmental disclosure timing and quality.
Inglese
Tarantino, M., Navigating a datascape: challenges in automating environmental data disclosure in China, <>, 2019; (N/A): 1-20. [doi:10.1080/09640568.2019.1659132] [http://hdl.handle.net/10807/142895]
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/10807/142895
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